Neuron pruning in temporal domain for energy efficient SNN processor design
Dongwoo Lew,
Hoyoung Tang,
Jongsun Park
Abstract:Recently, the accuracy of spike neural network (SNN) has been significantly improved by deploying convolutional neural networks (CNN) and their parameters to SNN. The deep convolutional SNNs, however, suffer from large amounts of computations, which is the major bottleneck for energy efficient SNN processor design. In this paper, we present an input-dependent computation reduction approach, where relatively unimportant neurons are identified and pruned without seriously sacrificing the accuracies. Specifically… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.